GCP / K8S DevOps Engineer

We're tackling a massive problem across the food supply chain: nearly half of all food grown in the US is wasted. That's why we're building an intelligent operations platform that transforms how food businesses work. Our technology helps growers and processors make smarter decisions, improve quality, and cut waste. If you're excited about using technology to create real-world impact in an essential industry and want to be part of a fast-moving, mission-driven team, we'd love to meet you. You're an experienced devops engineer (2-5 years) who has worked on production cloud environments in Google Cloud Platform (GCP) and Kubernetes (GKE). You have worked on deploying, maintaining and auto-scaling backend, database and frontend services. You are thinking about security and scalability. Responsibilities: • Orchestrating Cloud Infrastructure: Designing, deploying, and scaling resilient production environments on GCP using Kubernetes (GKE). • Automating Delivery: Building and maintaining robust CI/CD pipelines that enable seamless, automated deployments for backend, database, and AI services. • Scaling Data Systems: Managing and optimising high-performance databases, ensuring spatial data tools (like PostGIS and pg_tileserv) are performant, highly available and autoscaling. • Implementing Observability: Establishing comprehensive monitoring, logging, and alerting frameworks to ensure system health and rapid incident response. • Hardening Security: Managing IAM roles, network security (VPCs), and secret management to ensure a "security-first" architecture. • Optimising for Performance: Tuning container resources and cluster autoscaling to balance high-performance AI workloads with cost-efficiency. • Driving Infrastructure as Code: Ensuring all environments are reproducible and version-controlled using tools like Terraform or Helm. • Collaborating on Architecture: Partnering with backend and data engineering teams to design scalable microservices and reliable data ingestion workflows. Requirements: • Thrives in Cloud-Native Ecosystems: You can confidently navigate GKE, VPCs, and IAM, and you enjoy the challenge of optimising container orchestration for performance and cost. • Champions Infrastructure as Code (IaC): You believe that if a resource isn't defined in Helm (or Terraform/Pulumi), it doesn't truly exist. You strive for reproducible, version-controlled environments. • Champions Kubernetes for ML: You are comfortable managing GKE clusters optimised for ML workloads, including autoscaling GPU/TPU nodes and using orchestrators like Kubeflow or Argo Workflows. • Builds Robust CI/CD Pipelines: You are focused on reducing "time to production" by automating testing, security scanning, and deployment strategies (like Canary or Blue/Green) using tools like GitHub Actions, GitLab CI, or ArgoCD. • Prioritises "Security-Shift-Left": You integrate security into the design phase, managing secrets effectively and ensuring that least-privilege access is the default, not an afterthought. • Optimises for Observability: You don't just wait for things to break; you build the monitoring, logging, and alerting frameworks (using Prometheus, Grafana, or Google Cloud Operations) that keep the "Golden Signals" in check. • Solves Systemic Complexity: You are excited by the challenge of autoscaling backend microservices and databases, and you're always looking for ways to simplify the developer experience through internal tooling and automation. Good to Have: We're especially excited about candidates who bring: • Production K8S Expertise: Deep experience managing GKE at scale, including ingress controllers, service meshes (like Istio), and cost optimisation. • Database Reliability Background: Hands-on experience with PostgreSQL/PostGIS at scale, you know how to debug a slow query or a connection pooler just as well as a deployment script. • Infrastructure Automation Mastery: A "code-first" mindset with significant experience in Helm (or Terraform). • Linux and Networking Proficiency: A strong understanding of VPC networking, DNS, load balancing, and the Linux internals required to troubleshoot complex system issues. • Experience in SaaS Environments: Familiarity with the unique demands of a multi-tenant, dashboard-heavy product where data availability is mission-critical.